Physico-chemical and high frequency monitoring dataset from mesocosm experiments simulating extreme climate events in lakes

We present two datasets composed of high frequency sensors data, vertical in situ profiles and laboratory chemical analysis data, acquired during two different aquatic mesocosm experiments performed at the OLA (“Long-term observation and experimentation for lake ecosystems”) facility at the UMR CARRTEL in Thonon les Bains, on the French shore of Lake Geneva. The DOMLAC experiment lasted 3 weeks (4-21 October 2021) and aimed to simulate predicted climate scenarios (i.e. extreme events such as storms and floods) by reproducing changes in quality and composition of lake subsidies and runoff by increased inputs of terrestrial organic matter. The PARLAC experiment lasted 3 weeks (5-23 September 2022) and aimed to simulate turbid storms by light reduction. The experimental setup consisted of nine inland polyester laminated tanks (2.1 m length, 2.1 m width and 1.1 m depth) with a total volume of approximately 4000 L and filled with water directly supplied from the lake at 4m depth. Both experimental design included three treatments each replicated three times. The DOMLAC experiment involved a control treatment (no treatment applied) and two treatments simulating allochthonous inputs from two different dissolved organic matter (DOM) extract from peat moss Sphagnum sp. (Peat-Moss treatment) and Phragmites australis (Phragmite treatment). The PARLAC experiment involved a control treatment (no treatment applied) and two treatments simulating two different intensity of light reduction. In the Medium treatment transmitted light was reduced to 70% and in the High treatment transmitted light was reduced to 15%. The datasets are composed of: 1. In situ measures from automated data loggers of temperature, conductivity, dissolved oxygen and CO2 acquired every 5 minutes at 0.1, 0.5 and 1 m depth (DOMLAC) and 0.5m (PARLAC) for the entire period of the experiment. 2. In situ profiles (0-1 m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation) acquired twice a week during the experiment. 3. In situ measures of light spectral UV/VIS/IR irradiance (300-950 nm wavelength range) taken in the air and at 0, 0.5 and 1 m twice a week on the same day of the profiles at point 2. 4. Laboratory chemical analysis of integrated samples taken twice a week on the same day of the in situ profiles at point 2 and 3 of conductivity, pH, total alkalinity, NO3, total and particulate nitrogen (Ntot, Npart), PO4, total and particulate phosphorus (Ptot, Ppart), total and particulate organic carbon (TOC, POC), Ca, K, Mg, Na, Cl, SO4 and SiO2. Only for DOMLAC also analyses of NH4, NO2 and dissolved organic carbon (DOC). 5. Laboratory analysis of pigments (Chla, Chlc, carotenoids, phaeopigments) extracted from samples collected at point 4. 6. Only for DOMLAC, specific absorbance on the range 600-200nm of DOM (i.e. <0.7 µm) measured on samples collected at point 4. This dataset aims to contribute our understanding of how extreme climate events can alter lake subsidies and affect the regulation of ecosystem processes such as production, respiration, nutrient uptake and pigment composition. The data can be used for a wide range of applications as being included in meta-analysis aiming at generalising the effect of climate change on large lakes including simulating future scenarios in a broad range of geographical areas as we used different inputs of DOM leached from litters reproducing catchments characteristics typical of different latitudes, such as mostly dominated by large leaf forests and phragmites at middle latitude, and coniferous forests rich of peat mosses that spread along the water surface typical of Northern regions.


a b s t r a c t
We present two datasets composed of high frequency sensors data, vertical in situ profiles and laboratory chemical analysis data, acquired during two different aquatic mesocosm experiments performed at the OLA ("Long-term observation and experimentation for lake ecosystems") facility at the UMR CARRTEL in Thonon les Bains, on the French shore of Lake Geneva. The DOMLAC experiment lasted 3 weeks (4-21 October 2021) and aimed to simulate predicted climate scenarios (i.e. extreme events such as storms and floods) by reproducing changes in quality and composition of lake subsidies and runoff by increased inputs of terrestrial organic matter. The PARLAC experiment lasted 3 weeks (5-23 September 2022) and aimed to simulate turbid storms by light reduction. The experimental setup consisted of nine inland polyester laminated tanks (2.1 m length, 2.1 m width and 1.1 m depth) with a total volume of approximately 40 0 0 L and filled with water directly supplied from the lake at 4m depth. Both experimental design included three treatments each replicated three times. The DOMLAC experiment involved a control treatment (no treatment applied) and two treatments simulating allochthonous inputs from two different dissolved organic matter (DOM) extract from peat moss Sphagnum sp . (Peat-Moss treatment) and Phragmites australis (Phragmite treatment). The PARLAC experiment involved a control treatment (no treatment applied) and two treatments simulating two different intensity of light reduction. In the Medium treatment transmitted light was reduced to 70% and in the High treatment transmitted light was reduced to 15%. The datasets are composed of: 1. In situ measures from automated data loggers of temperature, conductivity, dissolved oxygen and CO 2 acquired every 5 minutes at 0.1, 0.5 and 1 m depth (DOMLAC) and 0.5m (PARLAC) for the entire period of the experiment. 2. In situ profiles (0-1 m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation) acquired twice a week during the experiment. 3. In situ measures of light spectral UV/VIS/IR irradiance (300-950 nm wavelength range) taken in the air and at 0, 0.5 and 1 m twice a week on the same day of the profiles at point 2. 4. Laboratory chemical analysis of integrated samples taken twice a week on the same day of the in situ profiles at point 2 and 3 of conductivity, pH, total alkalinity, NO 3 , total and particulate nitrogen (Ntot, Npart), PO 4 , total and particulate phosphorus (Ptot, Ppart), total and particulate organic carbon (TOC, POC), Ca, K, Mg, Na, Cl, SO 4 and SiO 2 . Only for DOMLAC also analyses of NH 4 , NO 2 and dissolved organic carbon (DOC). 5. Laboratory analysis of pigments (Chl a , Chl c , carotenoids, phaeopigments) extracted from samples collected at point 4. 6. Only for DOMLAC, specific absorbance on the range 60 0-20 0nm of DOM (i.e. < 0.7 μm) measured on samples collected at point 4. This dataset aims to contribute our understanding of how extreme climate events can alter lake subsidies and affect the regulation of ecosystem processes such as production, respiration, nutrient uptake and pigment composition. The data can be used for a wide range of applications as being included in meta-analysis aiming at generalising the effect of climate change on large lakes including simulating future scenarios in a broad range of geographical areas as we used different inputs of DOM leached from litters reproducing catchments characteristics typical of different latitudes, such as mostly dominated by large leaf forests and phragmites at middle latitude, and coniferous forests rich of peat mosses that spread along the water surface typical of Northern regions.
©  Table   Subject  Environmental Science -Ecology  Specific subject area  Physico-chemical and high frequency monitoring datasets produced during two  grounded base mesocosm experiments directly supplied with Lake Geneva water  Type of data  Tables  How data were

Value of the Data
• These datasets improve our understanding of the effect of environmental forcing on lake physico-chemical characteristics (such as temperature, oxygen and nutrient concentration) under simulated intense weather events. Additionally, the DOMLAC study evaluated the impact of increased input of Dissolved Organic Matter leached from different litter types such as peat moss and phragmites, representative of different geographic areas and reproducing organic matter gradients from Northern to middle latitudes. • This open and raw dataset will benefit the scientific community working on environmental ecology as can be used for a wide variety of applications including further metaanalysis aiming at generalising the effect of climate change across different regions and latitudes including catchments and lake shores with different characteristics. • These data provide a quality-assured baseline of key lake parameters measured using standardised methods that may help to discern changes in lake environmental status and assist in better managing and protecting lake ecosystems.

Objective
In the context of global warming, extreme precipitation and pluvial flooding are predicted to increase [6] . Persistent storm-induced changes in water clarity could be at least as important as rising air temperatures in determining lake responses to climate change [7 , 8] .
We initiated our mesocosm research during summer 2019 by running an in situ experiment in Lake Geneva [4 , 5] to simulate extreme events such a turbid storms. In the experimental treatments we applied manual mixing, increased DOC concentration and reduced light on two different intensity of stress (intermediate and intense) to test the effect on plankton diversity and the related functional traits. The intense treatment strongly affected the oxygen concentration [4] and community pigment composition [5] . The exchange of organic matter among ecosystems showed major impacts on plankton populations structure and dynamics [9] , yet little is known about how individual responses combine with the ecosystem feedback. To further investigate these questions we setup a ground based mesocosm system directly supplied with lake water and specifically designed to provide a comprehensive panel of measures that can be generalized to different temporal and spatial scales.
The projects DOMLAC and PARLAC were designed in the continuity of a series of different and complementary mesocosm experiments aiming to simulate future scenarios and disentangle how predicted increase precipitation affects plankton community composition, trophic transfer and the related ecosystem feedback on functional and metabolic process such as production, respiration and recycling. During extreme weather events different forcing are often occurring at the same time. The specific effect of stressors such as organic matter pulses and reduction in light penetration can be thus masked if one stressor acts in a stronger way. We simulated future scenarios by applying separately the main stressors occurring during turbid storms, such as different OM quality inputs (DOMLAC project) and light limitation (PARLAC) to understand the specific effect of each stressor.
Combining high-frequency monitoring with discrete measures, will allow elucidating the effect of extreme events at different scales (temporal, spatial) and organizational levels (community and food web).

Data Description
The datasets described in this section can be download at data repository INRAE. The data are stored as single excel file containing six (DOMLAC) and five (PARLAC) data sheets and two summary table sheets [2 , 3] .  In the DOMLAC dataset [2] the first rows of the sheets contain indication on the used device (row flagged by "# Device"), the depth of the measure (row flagged by "# Depth") and the unit of the measure (row flagged by "#"). Unique ID for each column (Sample_Name) includes the mesocosm treatment (named Control, Phragmite and Peat-Moss), replicate (from 1 to 3) and the sampling event (numbered S1 for 04.10.2021, S2 for 07.10.2021, S3 for 11.10.2021, S4 for 14.10.2021, S5 for 18.10.2021 and S6 for 21.10.2021), i.e. first row named S1_Control1 is the Control treatment, replicate 1 on the sampling day 1 04.10.2021. Samples labelled with "S1 + " in the column "Sample_Name" and "Sampling" are the TOC measures taken at the surface of all mesocosms few minutes after the DOC solution was added on 6 th of October 2021. Complete names abbreviations and sampling dates are in Table 1 .
Missing data and values below the limit of quantification are respectively identified by the code NA and LOQ.
In the PARLAC dataset [3] the first rows of the sheets contain indication on the used device (row flagged by "# Device"), the depth of the measure (row flagged by "# Depth") and the unit of the measure (row flagged by "#"). Unique ID for each column (Sample_Name) includes the mesocosm treatment, named Control, Medium (Medium light reduction, i.e. 70% transmitted light) and High (high light reduction, i.e. 15% transmitted light), replicate (from 1 to 3) and the sampling event (numbered S1 for 05.  Table 2 .
Missing data and values below the limit of quantification are respectively identified by the code NA and LOQ.
Pigments data: The fifth sheet (named "Pigments") contains data from laboratory analysis of pigments extracted from integrated samples and analysed using spectrophotometry after extraction into 90% acetone (ISO 10260: 1992).
In the DOMLAC dataset [2] only: Specific Absorbance data: The sixth sheet (named "Specific Absorbance") contains data from specific absorbance measured in the range 20 0-60 0 nm from integrated samples filtered on 0.7 μm Glass fiber filters and analysed using spectrophotometry.

Experimental Design
The mesocosm experiments was performed at the OLA-CARRTEL ground based experimental facility, located in Thonon les Bains, France. Nine polyester laminated thanks of dimensions 2.1 m length, 2.1 m width and 1.1 m depth (total volume about 40 0 0 L) are located on the shore of Lake Geneva and equipped with a pump and a pipe system which allows to fill simultaneously all experimental tanks with directly supplied lake water from 4m depth. The mesocosms were filled with a slow flow for about 8h and left to acclimate to the new conditions during one week (DOMLAC from 27.09.2021 until 03.10.2021 and PARLAC from 29.08.2022 until 04.09.2022). For the DOMLAC experiment on the second day of acclimation each mesocosm was inoculated with 3 plankton net tows (50 μm mesh, 0-20m) randomly taken simultaneously in the lake in front of the experimental facility. During the acclimation all the mesocosms were covered with a mosquito net and in the DOMLAC experiment for the entire experiment. The PARLAC mesocosm were each covered with a 2.1x2.1m lid with 1.2X1.2 light film according the treatment. Artificial mixing was induced during the entire acclimation and experiments with direct air bubbles from continuously releasing compressed air from a tube (6 mm diameter) placed at the bottom and in the centre of the mesocosms.
The DOMLAC experiment aimed to simulate predicted climate scenarios (i.e. extreme events such as turbid storms) by introducing inputs of dissolved organic matter (i.e. < 0.7 μm) leached from different litters, respectively peat moss and phragmites for the two treatments. The increase was done using the lake as reference (i.e. total DOC ∼ 1.2 mgL −1 ), and aiming at simulating the highest values measured in the Dranse tributary river during a flood, corresponding to 5x increased concentration, i.e. total DOC ∼ 6 mgL −1 .
The DOM extract was prepared using commercial bio peat moss ( Sphagnum sp. , Belgian company DCM) and phragmites ( Phragmites australis) collected on the Lake Geneva surroundings. The plants were dried in the air for 48h and grinded before being processed. 250g of plants or peat bog were mixed with 1.5L of ultra pure water and autoclaved for one hour at 120 °C. This solution was then centrifuged for 15 min at 3500 r/min and the supernatant filtered through 0.7 μm glass fiber filters. The final solution was autoclaved again before being added to the mesocosms.
The experiment lasted 3 weeks (4-22 October 2021), the first sampling (S1) took place on 04.10.2022 after the environmental acclimation (no treatments were applied yet at that moment). Treatments were applied on the 06.10.2022 by adding as single pulse the peat moss extract to the Peat-Moss treatments and the phragmites extract to the Phragmite treatment.
The PARLAC experiment aimed to simulate turbid storms by manipulating transmitted light using LEE ND (Neutral Density) filters, which reduce light without changing colour. The experimental design included three treatments each replicated three times: a control treatment (covered with a ∼95% transmitted light filter to expose all the mesocosms to the same covering condition) and two different treatments simulating two different intensity of light reduction. In the Medium treatment transmitted light was reduced to ∼70% and in the High treatment transmitted light was reduced to ∼15%. The experiment lasted 3 weeks (5-23 September 2022), the first sampling (S1) took place on 05.09.2022 after the environmental acclimation (no treatments were applied yet at that moment). After the first sampling the treatments were applied by placing the light filters on all the mesocosms.

Instrumentation
Continuous monitoring data were acquired using data loggers including: Temperature: Campbell, HOBO, MiniDOT Conductivity: CS547A-L -Campbell Scientific Dissolved oxygen: MiniDOT CO 2 : Vaisaila GMP252 MiniDOT and HOBO are autonomous sensors and were ready for deployment. Temperature, conductivity and CO 2 (CS547A-L -Campbell Scientific) are analog sensors and needed to be connected to data loggers. In the DOMLAC experiment data loggers Campbell CR10x were used in C1, CR10 0 0 in Phragmite1 treatment and CR10 0 0x for Peat-Moss1 treatment. In the PARLAC experiment data loggers Campbell CR10x were used in C1 and M1 treatment and CR10 0 0 for H1 treatment.
Temperature sensors were calibrated in an environmental chamber. For Campbell and MiniDOT, calibration data were updated via the software.
Conductivity sensors were calibrated using a potassium chloride standard solution of 294 μS/cm at 25 ºC. The calibration included temperature compensation.
Oxygen sensors were controlled at 100% saturation in water taking into account the barometric pressure.
CO 2 sensors were calibrated in the air and in a closed chamber with standard gas at 500ppm. The intercalibration was done with certified reference CO 2 sensor (AMT).
In-situ vertical profiles data for physical characterisation of each mesocosm included in situ profiles (0-1 m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation) acquired using a multiparameter probe CTD 90M. Light spectral measurements of UV, VIS, IR irradiance (300-950 nm wavelength range) were taken on the air above the mesocosm, at 0, 0.5 and 1 m using a RAMSES-ASC-VIS irradiance sensor.
Integrated samples (0-1 m) for laboratory chemical analysis were collected on the same day of in situ vertical profile data according protocols and methods detailed in [1] .
Conductivity was measured using conductometric method. Temperature corrections are systematically applied when performing lab measurements of the conductivity (ISO 10523:2008). pH was measured with an automatic titrator (Basic Titrino 794, Metrohm ©) with a glass electrode.
Pigments measured in integrated samples using spectrophotometry after extraction into 90% acetone (ISO 10260: 1992). Specific absorbance measured in the range 20 0-60 0 nm in integrated samples filtered on 0.7 μm glass fiber filters and analysed using spectrophotometry.
Data forms or acquisition methods : In situ profiles and discrete samples for data analyses were collected twice a week during the experiment. Data from the automated probes are provided in the form of csv or txt files and were downloaded after each sampling event. Water samples for chemical analyses were stored at 4 °C and the analyses were performed within 48 h after collection.
Data entry verification procedures : In-situ data are collected and visually checked by the operator after each time of conducting the probes. They are crossed checked by a second operator using the original field data sheets. Laboratory analysis data are collected and manually checked by the operator and validated by authorized scientific staff.
Quality assurance/quality control procedures : In-situ data are manually validated and crossed validated with laboratory analysis (pH, Cond, dissolved oxygen).
The analytical quality control of laboratory data follows a rigorous traceable workflow from sample collection to data validation. Data are controlled by an analytical quality monitoring of instruments, a verification with reference materials and manual cross-validation between chemist staff.
Data anomalies : Negative values of light spectral measurement are detected near 300 nm wavelengths. According to manufacturer' specifications, negative values can be included in uncertainty interval.
Computer programs and data-processing algorithms : For data formatting, homogenization and first visualization we used the software R. Data outliers were mostly manually identified based on quality assurance and quality control procedures (previous section).

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships, which have, or could be perceived to have, influenced the work reported in this article.

Data Availability
Physico-chemical and high frequency monitoring dataset from a mesocosm experiment simulating turbid storms by light reduction (Original data) (Dataverse).